In this study, a novel lifting motion simulation model was developed based on a multi-objective optimization (MOO) approach. Two performance criteria, minimum physical effort and maximum load motion smoothness, were selected to define the multi-objective function in the optimization procedure using a weighted-sum MOO approach. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. The results showed that the proposed MOO approach led to up to 18.9% reductions in the prediction errors compared to the single-objective optimization approach. This finding suggests that both minimum physical effort and maximum load motion smoothness play an important role in lifting motion planning. Age-related differences in the mechanisms for planning lifting motions were also investigated. In particular, younger workers tend to rely more on the criterion of minimizing physical effort during lifting motion planning, while maximizing load motion smoothness seems to be the dominant objective for older workers. Relevance to industryLifting tasks are closely associated with occupational low back pain (LBP). In this study, a novel lifting motion simulation model was developed to facilitate the analysis of lifting biomechanics and LBP prevention. Age-related differences in lifting motion planning were discussed for better understanding LBP injury mechanisms during lifting.